class_docstr: QA dataset with common knowledge facts.
code: def _info(self):
      return self.dataset_info_from_configs(
          features=tfds.features.FeaturesDict(
              {
                  "question": {
                      "stem": tfds.features.Text(),
                      "choice_A": tfds.features.Text(),
                      "choice_B": tfds.features.Text(),
                      "choice_C": tfds.features.Text(),
                      "choice_D": tfds.features.Text(),
                  },
                  "fact1": tfds.features.Text(),
                  "humanScore": tfds.features.Tensor(
                      shape=(), dtype=np.float32
                  ),
                  "clarity": tfds.features.Tensor(
                      shape=(), dtype=np.float32
                  ),
                  "turkIdAnonymized": tfds.features.Text(),
                  "answerKey": tfds.features.ClassLabel(
                      names=["A", "B", "C", "D"]
                  ),
              }
          ),
          # If there's a common (input, target) tuple from the features,
          # specify them here. They'll be used if as_supervised=True in
          # builder.as_dataset.
          supervised_keys=("question", "answerKey"),
          # Homepage of the dataset for documentation
          homepage="https://leaderboard.allenai.org/open_book_qa/submissions/get-started",
      )
  
file_path: datasets/tensorflow_datasets/datasets/openbookqa/openbookqa_dataset_builder.py
imports: import json
  import os
  from etils import epath
  import numpy
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling the Builder obj's underlying member method code with example usage: obj._info() and returns: self